
<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Soobin Kim</style></author><author><style face="normal" font="default" size="100%">Yongsung Kwon</style></author><author><style face="normal" font="default" size="100%">JongCheol Pyo</style></author><author><style face="normal" font="default" size="100%">Mayzonee Ligaray</style></author><author><style face="normal" font="default" size="100%">Joong-Hyuk Min</style></author><author><style face="normal" font="default" size="100%">Jung Min Ahn</style></author><author><style face="normal" font="default" size="100%">Sang-Soo Baek</style></author><author><style face="normal" font="default" size="100%">Kyung Hwa Cho</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Developing a cloud-based toolbox for sensitivity analysis of a water quality model</style></title><secondary-title><style face="normal" font="default" size="100%">Environmental Modelling &amp; Software</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://doi.org/10.1016/j.envsoft.2021.105068</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">141</style></volume><pages><style face="normal" font="default" size="100%">105068</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">The complexity associated with water&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/quality-model&quot; title=&quot;Learn more about quality models from ScienceDirect's AI-generated Topic Pages&quot;&gt;quality models&lt;/a&gt;&amp;nbsp;(WQMs) has increased owing to the introduction of numerous physical and biological mechanisms in the models. Sensitivity analysis (SA) is conducted to identify influential parameters in these mechanisms. However, enormous computational power and time are required to obtain numerical solutions from thousands of model simulations. Therefore, a cloud-based toolbox is developed for performing SA of WQMs by implementing a&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/cloud-computing-system&quot; title=&quot;Learn more about cloud computing system from ScienceDirect's AI-generated Topic Pages&quot;&gt;cloud computing system&lt;/a&gt;&amp;nbsp;using grab sampling data and&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/hyperspectral-image&quot; title=&quot;Learn more about hyperspectral images from ScienceDirect's AI-generated Topic Pages&quot;&gt;hyperspectral images&lt;/a&gt;&amp;nbsp;(HSI) of waterbodies.&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/cloud-computing&quot; title=&quot;Learn more about Cloud computing from ScienceDirect's AI-generated Topic Pages&quot;&gt;Cloud computing&lt;/a&gt;&amp;nbsp;can provide high-performance computation by adjusting the scale of the computational power according to user preference. The developed toolbox with the&amp;nbsp;&lt;a href=&quot;https://www.sciencedirect.com/topics/computer-science/cloud-system&quot; title=&quot;Learn more about cloud system from ScienceDirect's AI-generated Topic Pages&quot;&gt;cloud system&lt;/a&gt;&amp;nbsp;can reduce the computation time for SA by approximately 20 times compared to that of a desktop computer.</style></abstract></record></records></xml>